An algorithm based on statistics and rules is proposed to automatically identify maximal-length evaluation phrase. The identification of evaluation phrase is taken as sequence tagging problem. Then conditional random field model is used to recognize evaluation phrase with simple structure. Therefore, rule database is established and maximal-length evaluation phrase with complex structure is identified automatically. F-measure value reaches 72.38%. Based on the above work, rule base is constructed for extracting opinon target and appraisal expression. Rule-based extracting appraisal expression is proposed to automatically extract opinion target and maximal-length evaluation phrase. Experiments were conducted at netease car portal and got a higher precision.